Official Standings

**This thread is to discuss hypothetical scenarios. It is not to discuss whether LSU has the ability to go undefeated or not. Also, we realize there is a lot of games left. Fortunately, as fans we can enjoy "looking ahead" as much as we want.

BCS STANDINGS BREAKDOWN

Here a best guess of the BCS standings (updated at 2:00 pm). Only the Coaches and Sagarin have been released, so there is a lot of guess work on my part. The top 5 (and especially the top 3) are really close and could finish in any order.

1. Oklahoma could be anywhere 1-3, but I think they may take the top spot. One would expect they control their own destiny with a relatively difficult schedule (Big12CG and FSU OOC), but it could be a dog fight with Oregon and LSU/AU if it came to that.

2. Oregon. The Pac10 is strong this year but lack of CG could hurt them if it cam down to 3 major undefeateds. Style points should help them in the polls though.

3. Boise State. And so it begins. They could hold on to #1 this week, but I have them beginning their slip. I was starting to buy into them having a shot. Then Oregon State lost as did Nevada (they needed Nevada). How does undefeated Boise fair against 1-loss Bama or LSU? It will be interesting.

4. Auburn. Big win over Arky bumped them up. One would think an undefeated SEC team is in easily, although OU and UO could be interesting.

5. TCU. TCU plays a bit of a tougher schedule than Boise so should fair better in the computers in the long run. They need Utah to keep winning. In the end, I think they share Boise's fate, but could be better off against a 1-loss teams

6. LSU. Playing McNeese (and struggling) should have little effect on LSU's current or future ranking. Beat AU and they shoot up to #3 or better.

7. MSU. Climbing the polls and computers, but they play no CG, skip out on OSU, don't play a super tough OOC opponent, and well, they are MSU.

8. Bama. Best position as a 1-loss obviously.

9. Utah. That Utah/TCU matchup gets more interesting everyday

10. OSU. Need a lot of help for a NC

HOW COMPUTER POLLS WORK

There is always chatter about the computer polls early and how they look bizarre. Many use it as an opportunity to discount the validity of them (and the BCS altogether). But remember, this is a STRENGTH of the computer polls; the fact they don’t have predetermined bias for teams based on what conference they play, how many National Titles they won in the 50s or if they are supposed to be good this year. If North Texas and Florida win their first game and start 1-0, they should be ranked the same (or close to it), because the computers don’t assume Florida was supposed to be better, nor does it assume their wins were better (even if Florida beat USC and North Texas beat ULM). As the season progresses, SOS can be determined more accurately and that Florida win over USC can be given more weight. Ultimately its SOS (however that poll determines it) is used to distinguish teams of like records. Remember SOS isn’t determined by what the Coaches poll thinks are the good teams, it is determined by what has been accomplished on the field this year.

In short, I don’t really trust any computer poll that DOESN'T look bizarre the first few weeks of the season. The Billingsly poll actually does use a “preseason” ranking which is his final poll from the previous year. It is based on a little more common sense, but I still find it unfair, and 90% of the time it is excluded from the BCS as an outlier. Sagarin and Massey also use “preseason” polls which make their polls look sensible early on, but both claim to drop that data by week 5. Anybody interested in how computer polls work should visit colleyrankings.com, Dr. Colley gives an excellent description of his poll and how and why it isn’t biased. There is a lot of math, but even if you get lost, the introduction is excellent.

TD.COM COMPUTER POLLS AND MOCK BCS

Several of your fellow posters produce excellent computer polls. The Tuba 101 has been a staple of TD.com for years. Xiv produces one also; both polls give outlandish results the first few weeks – a mark of a great computer poll imo! I have created my own also, the basic principle being that if two teams play there is a probability each team will win. The binger the difference in ranking, the greater chance the better team will win. I then solve a bunch of simultaneous equations (120, one for each team) which equates the expected wins (based on probability) with the actual wins for a team. Last we mergeg the td.com computer polls with the TD top 10 to create a mock BCS. We may do the same. I will release the lsumatt poll as soon as I can

THE EFFECT OF 1AA AND OTHER “WEAK TEAMS”

Strength of schedule is an inherent part of computer polls. It is how it is determined which team with the same record should be rated higher (or if 2-loss LSU should be higher than undefeated Hawaii). One misconception is that playing a 1AA team or a weak team actually hurts you; that you would be better off not playing a game at all. The thought process is that it brings down the average SOS of your team. For the most part, this just isn’t true. Beating McNeese State won’t help LSU’s rating much at all (if any), but rarely, if ever, will it hurt you in the computers (other teams may jump LSU because they improved their rating with a tough opponent but would have done the same if LSU had a BYE). After all, beating a 1AA team is still (slightly) tougher than beating OPEN DATE. A couple computer polls ignore 1AA games altogether and treat them as an open date.

A DESCRIPTION OF THE BCS POLLS

Most of the BCS polls use an “iterative” strategy: the guess all the teams ranking, determine SOS based on that, re-calculate the ranking, and repeat until there is no change (and no, it doesn’t matter what their initial guess is). They don’t use MOV and the final poll doesn’t use any preseason bias (except Billingsly). Here is my best description of the computer polls (only Billingsly and Colley explain their ratings)

COLLEY MATRIX ( COLLEY). My favorite poll, because it is mathematically sound and he describes it in detail (see his pdf online). He basically sets up 120 equations and solves them. His algorithm is spelled out so well, we can (and I do) re-create his poll. I also have a “future poll” in which I predict the final Colley matrix based on expected outcomes of future games.

BILLINGSLY. What I call the “common sense” poll. The math is simple and he uses a preseason poll (last year’s final poll). He explains in detail on his website. He also does something different in which strength of schedule is a hybrid of a team’s current ranking and their final ranking. So if you beat Ole Miss in week 2, but then end up 5-7 you get some credit for beating a top 10 team. He claims top10 “feel” of the game, is important. Regardless, his poll is almost always excluded as an outlier.

SAGARIN. I hate this poll, mostly because he refuses to explain it at all. Also, I am suspicious of his preseason ranking (which he claims to drop). He has two polls: the predictor which uses MOV and elochess which doesn’t…it is elochess that is included in the BCS). Sagarin also includes a Home/Away component which I think is good. Also, empirical evidence suggests that a bad loss in Sagarin weighs you like an anchor. For example, losing to 4-8 Tenn is 2005 killed LSU.

ANDERSON and HESTER. Another iterative poll that gives sensible rankings by the end. He doesn’t release until midseason because they would look bizarre. He appears to give bonus points for wins over top 10 and top 25 teams (in his own poll, not the human polls).

MASSEY Uses a preseason poll, but claims to drop it mid season when things get connected. It appears to be a traditional iterative poll.

WOLFE. Another iterative poll, that isn’t released till mid season. His website is an excellent place to get data of scores of all games of the season.

TUBA 101, XIV, and LSUMATT POLL. All being wooed by the BCS, but we are holding out for a better offer.